Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants

A Master of Science thesis in Chemical Engineering by Wasim Ahmed entitled, "Modeling, Simulation, and Control of Biotrickling Filter for Removal of Air Pollutants," submitted in June 2012. Thesis advisor is Dr. Zarook Shareefdeen and thesis co-advisor is Dr. Nabil Abdel Jabbar. Available...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ahmed, Wasim (author)
التنسيق: doctoralThesis
منشور في: 2012
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/4074
الوسوم: إضافة وسم
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author Ahmed, Wasim
author_facet Ahmed, Wasim
author_role author
dc.contributor.none.fl_str_mv Shareefdeen, Zarook
Abdel Jabbar, Nabil
dc.creator.none.fl_str_mv Ahmed, Wasim
dc.date.none.fl_str_mv 2012-09-16T07:58:34Z
2012-09-16T07:58:34Z
2012-06
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2012.20
http://hdl.handle.net/11073/4074
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Mathematical modeling
Step response model
Neural network model
Conventional control strategies
Advanced control
Air quality management
Methodology
Air
Pollution
Research
Biotrickling filters
Biofiltration
dc.title.none.fl_str_mv Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Chemical Engineering by Wasim Ahmed entitled, "Modeling, Simulation, and Control of Biotrickling Filter for Removal of Air Pollutants," submitted in June 2012. Thesis advisor is Dr. Zarook Shareefdeen and thesis co-advisor is Dr. Nabil Abdel Jabbar. Available are both soft and hard copies of the thesis.
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network_acronym_str aus
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oai_identifier_str oai:repository.aus.edu:11073/4074
publishDate 2012
repository.mail.fl_str_mv
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spelling Modeling, Simulation and Control of Biotrickling Filter for Removal of Air PollutantsAhmed, WasimMathematical modelingStep response modelNeural network modelConventional control strategiesAdvanced controlAir quality managementMethodologyAirPollutionResearchBiotrickling filtersBiofiltrationA Master of Science thesis in Chemical Engineering by Wasim Ahmed entitled, "Modeling, Simulation, and Control of Biotrickling Filter for Removal of Air Pollutants," submitted in June 2012. Thesis advisor is Dr. Zarook Shareefdeen and thesis co-advisor is Dr. Nabil Abdel Jabbar. Available are both soft and hard copies of the thesis.Stringent environmental regulations for control of pollutants have led to the use of effective air pollution control strategies. Biotrickling filter, one of the biological reactors, offers a great advantage of being a cost effective and environmental friendly technology. This emerging technology has not yet received widespread application. Moreover, there is still a need to develop an appropriate biotrickling filter model for general acceptance and equally important to design an optimum control strategy before utilizing this technology on a large scale. Hence, this thesis aims to develop a representative dynamic model for the biotrickling filter based on the review of existing models, provide accurate analytical and numerical solution of the model under different conditions, and also select an optimum control strategy amongst the different control systems designed in this study. A theoretical model was selected, validated and modified to account for continuous, larger biotrickling filter. The modified model was solved using the pseudo-steady state assumption to reduce computational effort and time. Based on sensitivity analysis of the modified model, it was found that gas velocity and inlet concentration had strong effect on the outlet concentration of biotrickling filter. To implement the control strategies, simple data driven models were obtained using the data from simulation of the modified model. These data driven models were needed since the modified model simulation would require considerable computational effort and time. In particular, transfer function and neural network models were successfully obtained with R2 values above 0.97. Five control strategies were designed, implemented and analyzed through set-point and disturbance changes. Three of the five controllers were based on transfer function biotrickling filter model while the rest used steady state neural networks as the biotrickling filter plant model. Overall, it was found that the proportional-integral, proportional-integral with feedforward and the transfer function based model predictive controllers provided satisfactory system performance. In case of the neural network based model predictive controller, excellent set-point tracking had been observed but an offset error had been observed in case of disturbance change. While the addition of an integral controller to the neural network based model predictive controller eliminated the offset errors, large overshoots had been observed in response to both set-point and disturbance changes. Search Terms: biotrickling filter, mathematical modeling, step response model, neural network model, biotrickling filter control strategies, conventional control strategies, advanced controlCollege of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE)Shareefdeen, ZarookAbdel Jabbar, Nabil2012-09-16T07:58:34Z2012-09-16T07:58:34Z2012-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2012.20http://hdl.handle.net/11073/4074en_USoai:repository.aus.edu:11073/40742025-06-26T12:30:44Z
spellingShingle Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
Ahmed, Wasim
Mathematical modeling
Step response model
Neural network model
Conventional control strategies
Advanced control
Air quality management
Methodology
Air
Pollution
Research
Biotrickling filters
Biofiltration
status_str publishedVersion
title Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
title_full Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
title_fullStr Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
title_full_unstemmed Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
title_short Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
title_sort Modeling, Simulation and Control of Biotrickling Filter for Removal of Air Pollutants
topic Mathematical modeling
Step response model
Neural network model
Conventional control strategies
Advanced control
Air quality management
Methodology
Air
Pollution
Research
Biotrickling filters
Biofiltration
url http://hdl.handle.net/11073/4074